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Related Concept Videos

Ischemic Heart Disease: Overview01:17

Ischemic Heart Disease: Overview

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Ischemic heart disease occurs when the heart's blood supply dwindles, causing an ominous lack of oxygen and nutrients. This deficiency, stemming from reduced or obstructed blood flow, spells danger, leading to heart muscle damage and dysfunction.
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Coronary Artery Disease I: Introduction01:30

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Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
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Coronary Artery Disease IV: Preventive Measures01:26

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Effective preventive measures for coronary artery disease (CAD) focus on controlling modifiable risk factors, including cholesterol abnormalities and lifestyle changes.Cholesterol ManagementFirst, the Mediterranean diet and the American Heart Association advocate for maintaining low-density lipoprotein (LDL) cholesterol levels below 100 mg/dL, with a more stringent recommendation of below 70 mg/dL for individuals at high risk. LDL cholesterol, often termed "bad cholesterol," can lead to the...
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Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

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Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
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Assessment of the Cardiovascular System I: Subjective Data01:23

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A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
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Medical History
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Coronary Artery Disease II: Pathophysiology01:26

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Coronary Artery Disease (CAD) originates from a series of events that impair the function of coronary arteries, the blood vessels responsible for delivering oxygen-rich blood to the heart muscle. The pathophysiology of CAD is closely linked to atherosclerosis, a chronic inflammatory and lipid-driven condition affecting the vascular endothelium.1. Endothelial DamageThe process begins with damage to the vascular endothelium, which serves as a protective barrier between the blood and the vessel...
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Updated: May 5, 2026

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Women's Cardiovascular Disease and Stroke Risk Stratification Using a Precision and Personalized Framework Embedded

Ekta Tiwari1, Dipti Shrimankar1, Mahesh Maindarkar2

  • 1Department of Computer Science and Engineering, Vishvswarya National Institute of Technology, Nagpur 440010, India.

Diagnostics (Basel, Switzerland)
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Summary

Artificial intelligence (AI) and machine learning (ML) can improve cardiovascular disease (CVD) risk assessment in women by integrating diverse health data. This approach addresses limitations of traditional tools in detecting female-specific risk factors for better personalized care.

Keywords:
autoimmune diseasescarotid ultrasoundhormonal factorsmachine learning and deep learningpregnancy complicationswomen’s CVD risk stratification

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Area of Science:

  • Cardiovascular Medicine
  • Biomedical Engineering
  • Artificial Intelligence

Background:

  • Women experience underdiagnosed cardiovascular disease (CVD) and stroke risks due to unique pathophysiological factors like hormonal changes and adverse pregnancy outcomes (APOs).
  • Existing CVD risk assessment tools are primarily designed for male physiology, failing to capture female-specific determinants.
  • Hormonal variations, endothelial dysfunction, and autoimmune factors contribute to CVD risk in women.

Purpose of the Study:

  • To explore the potential of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in enhancing CVD and stroke risk stratification for women.
  • To investigate the integration of multimodal data, including biomarkers, clinical history, and vascular imaging, for precision risk assessment.
  • To address the limitations of conventional risk assessment tools in detecting female-specific CVD risk factors.

Main Methods:

  • A narrative review using a PRISMA-informed framework to analyze gender-specific biomarkers (e.g., hs-CRP, adiponectin, homocysteine) and clinical variables (e.g., APOs).
  • Inclusion of ultrasonographic markers like carotid intima-media thickness (cIMT) and plaque area (PA).
  • Application of advanced ML/DL algorithms to synthesize heterogeneous datasets and identify nonlinear interactions for improved CVD risk prediction.

Main Results:

  • Hormonal fluctuations, particularly post-menopausal hypoestrogenism, significantly modulate CVD risk in women.
  • Adverse pregnancy outcomes (APOs) are linked to persistent endothelial dysfunction and subclinical atherosclerosis.
  • Biomarker sexual dimorphism observed, with higher hs-CRP in women and declining adiponectin with metabolic dysfunction. Radiomic features of cIMT and plaque morphology are key risk indicators.

Conclusions:

  • AI-driven multimodal systems offer a paradigm shift towards personalized CVD risk assessment, crucial for addressing gaps in women's cardiovascular health.
  • Current AI applications for female CVD risk stratification are in early validation stages.
  • Future research requires prospective, externally validated, and diverse studies incorporating longitudinal biomarker profiling and advanced imaging techniques like shear wave elastography and plaque radiomics.